Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Ruya Sun

dblp:226/9986 · DBLP profile ↗
← Back
3ranked-venue papers
1as first author
3since 2021 · last 2025
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Rendering · 67% Computational photography and imaging · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational photography and imaging › active illumination
illumination multiplexing
0.912025
Sparse SVBRDF Acquisition via Importance-Aware Illumination Multiplexing · ACM Trans. Graph. 2025
Rendering
reflectance modeling
0.912025
Sparse SVBRDF Acquisition via Importance-Aware Illumination Multiplexing · ACM Trans. Graph. 2025
Rendering › appearance acquisition › material acquisition
SVBRDF acquisition
0.912025
Sparse SVBRDF Acquisition via Importance-Aware Illumination Multiplexing · ACM Trans. Graph. 2025

Methods — techniques the papers use, named apart from their topics

neural network · 0.9microfacet theory · 0.9importance sampling · 0.9adaptive sampling · 0.9
YearPublicationVenuePosition
2025 On-site single image SVBRDF reconstruction with active planar lighting
Lianghao Zhang 0001, Ruya Sun, Li Wang 0131, Fangzhou Gao, Jiawan Zhang
Comput. Graph.2
2025 Sparse SVBRDF Acquisition via Importance-Aware Illumination Multiplexing
abstract
Reflectance acquisition from sparse images has been a long-standing problem in computer graphics. Previous works have addressed this by introducing either material-related priors or illumination multiplexing with a general sampling strategy. However, fixed lighting patterns in multiplexing can lead to redundant sampling and entangled observations, making it necessary to adaptively capture salient reflectance responses in each shot based on material behavior. In this paper, we propose combining adaptive sampling with illumination multiplexing for SVBRDF reconstruction from sparse images lit by a planar light source. Central to our method is the modeling of a sampling importance distribution on lighting surface, guided by the statistical nature of microfacet theory. Based on this sampling structure, our framework jointly trains networks to learn an adaptive sampling strategy in the lighting domain, and furthermore, approximately separates pure specular-related information from observations to reduce ambiguities in reconstruction. We validate our approach through experiments and comparisons with previous works on both synthetic and real materials.
Lianghao Zhang 0001, Li Wang 0131, Fangzhou Gao, Ruya Sun, Jiawan Zhang
ACM Trans. Graph.5
2021 Comparative analysis of aneurysm subtypes associated genes based on protein-protein interaction network
abstract
The arterial aneurysm refers to localized dilation of blood vessel wall and is common in general population. The majority of aneurysm cases remains asymptomatic until a sudden rupture which is usually fatal and of extremely high mortality (~ 50-60%). Therefore, early diagnosis, prevention and management of aneurysm are in urgent need. Unfortunately, current understanding of disease driver genes of various aneurysm subtypes is still limited, and without appropriate biomarkers and drug targets no specialized drug has been developed for aneurysm treatment. In this research, aneurysm subtypes were analyzed based on protein-protein interaction network to better understand aneurysm pathogenesis. By measuring network-based proximity of aneurysm subtypes, we identified a relevant closest relationship between aortic aneurysm and aortic dissection. An improved random walk method was performed to prioritize candidate driver genes of each aneurysm subtype. Thereafter, transcriptomes of 6 human aneurysm subtypes were collected and differential expression genes were identified to further filter potential driver genes. Functional enrichment of above driver genes indicated a general role of ubiquitination and programmed cell death in aneurysm pathogenesis. Especially, we further observed participation of BCL-2-mediated apoptosis pathway and caspase-1 related pyroptosis in the development of cerebral aneurysm and aneurysmal subarachnoid hemorrhage in corresponding transcriptomes.
Ruya Sun, Qinghua Cui
BMC Bioinform.1